A Hybrid Cache Architecture for Meeting Per-Tenant Performance Goals in a Private Cloud

Taejoon Kim, Yu Gu, Jinoh Kim

The in-memory cache system is an important component in a cloud for the data access performance. As the tenants may have different performance goals for data access depending on the nature of their tasks, effectively managing the memory cache is a crucial concern in such a shared computing environment. Two extreme methods for managing the memory cache are unlimited sharing and complete isolation, both of which would be inefficient with the expensive storage complexity to meet the per-tenant performance requirement. In this paper, we present a new cache model that incorporates global caching (based on unlimited sharing) and static caching (offering complete isolation) for a private cloud, in which it is critical to offer the guaranteed performance while minimizing the operating cost. This paper also presents a cache insertion algorithm tailored to the proposed cache model. From an extensive set of experiments conducted on the simulation and emulation settings, the results confirm the validity of the presented cache architecture and insertion algorithm showing the optimized use of the cache space for meeting the per-tenant performance requirement.

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